In addition, SMAP 2017 seeks papers for special sessions addressing emerging issues in all above aspects that will complement the regular program. Authors will have the opportunity to present their work in short papers that will appear in the official SMAP 2017 workshop proceedings.

SMAP 2017 has the support of the IEEE Computational Intelligence Society technical co-sponsorship.

*Special session on Personalized delivery of cultural heritage content
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Digital cultural heritage is now a mature field, in which information technologies are used in the service of preserving cultural heritage. The digital form of resources allows for the exploitation of advances in data analytics, semantics, information retrieval, user interaction, profiling and personalization in order to develop new, exciting and stimulating exhibitions and cultural/educational/touristic experiences.

For this special session we invite works that present and/or review the current state of the art in theory and practice, as well as promising recent advances, in the area of aligning the delivery process for cultural heritage content to the needs, goals, characteristics and preferences of individual users and user groups. The session is broad in scope, with the caveat that emphasis should be on the link between cultural heritage and personalization techniques.

*Special Session on Multimodal affective analysis for human-machine interfaces and learning environments
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Affective analysis is a broad research area that focuses on the recognition, interpretation, processing and simulation of human affect, i.e., feelings or emotions. During the last years many efforts in the fields of content understanding and human-machine interaction have turned towards a more human-centered approach and complement traditional semantic-based ones by enhancing them with the users’ affective state while interacting with machines (typically computers, avatars and robots).

This special session calls for research papers focusing on signal analysis and machine learning techniques that extract affective knowledge from auditory, visual and textual information usually employed in human-machine interaction and learning applications. Papers that focus on new signal representation, feature extraction and emotion modelling approaches are welcomed, as well as papers covering practical work, tools and applications.

*Proceedings/Publications
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As with all previous editions of SMAP, all accepted papers are planned to be published by IEEE in IEEEXplore. Based on the quality of the work presented and its estimated potential selected papers will be invited for consideration, in a revised and extended form, for inclusion in an additional journal publication.

*Submission guidelines
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Each submitted paper will be refereed by at least three members of the SMAP 2017 Program Committee, based on its relevance, originality, significance, technical soundness and clarity of expression. Submissions must be in English, and can present mature research or experimental results as well as promising work in progress. Papers must be formatted according to the IEEE 2-column conference article style, with a limit of 6 pages, including all figures, tables and references. A minimum paper length of 4 pages is also imposed.

GENERAL CHAIRS
Maria Bielikova, Slovak University of Technology in Bratislava
Marian Simko, Slovak University of Technology in Bratislava

SPECIAL SESSIONS CHAIRS
Ioannis Anagnostopoulos, University of Thessaly
Iraklis Paraskakis, The University of Sheffield, International Faculty CITY College, Greece

PUBLICITY CHAIR
Sebastien Laborie, University of Pau

LOCAL ORGANIZING CHAIR
Milena Zeithamlova, Action M Agency

WEB CHAIR
Patrik Hlavac, Slovak University of Technology in Bratislava

STEERING COMMITTEE
Ioannis Anagnostopoulos, University of Thessaly
Maria Bielikova, Slovak University of Technology in Bratislava
Sébastien Laborie, University of Pau
Martin Lopez-Nores, University of Vigo
Phivos Mylonas, Ionian University
Yannick Naudet, Luxembourg Institute of Science and Technology
Nicolas Tsapatsoulis, Cyprus University of Technology
Manolis Wallace, University of the Peloponnese